|8 days ago||about 1 month ago|
|GNU General Public License v3.0 or later||Apache License 2.0|
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I created a way to learn machine learning through Jupyter
2 projects | reddit.com/r/learnmachinelearning | 30 Apr 2021
There are actually some online books and courses built on Jupyter Notebook ([Dive to Deep Learning Book](https://github.com/d2l-ai/d2l-en) for example). However yours is more detail and could really helps beginners.
What are some alternatives?
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
ssd_keras - A Keras port of Single Shot MultiBox Detector
jina - Cloud-native neural search framework for 𝙖𝙣𝙮 kind of data
ScanRefer - [ECCV 2020] ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
DeepCamera - AI Face Recognition/Person Detection NVR. Machine Learning On The Edge, turn your Camera into AI-powered with Jetson Nano and telegram to protect your privacy.
einops - Deep learning operations reinvented (for pytorch, tensorflow, jax and others)